 :     
 

 


     .      ,      .       .     ,       .                   .





 :     



 

 



  

   



 ,2019

 ,2019

 ,  ,2019



ISBN978-5-4496-4829-7

     Ridero







     .      , ,   . ,   ,          .

     .        ,     .            , , .      , ,        ,   .

    :   .    ,    ,   ,   -   ,    .       , ,  .

  ,         ?       .

   .          .            (International Federation ofRobotics, IFR)       .            ,       ().

      蠖    ,     .            ,   : , ,  , .

       .    ,      ,        .  ,   ,       ,                  .      ,      ,       .

       ,                    .    ,     ,    ,         .




1.  



ࠖ    ,    .  The Robot Report[1 - Kara D. July 2018Robotics and Intelligent Systems Investments. The Robot Report [ ] URL: https://www.therobotreport.com/july-2018-robotics-and-intelligent-systems-investments (https://www.therobotreport.com/july-2018-robotics-and-intelligent-systems-investments).],  2018 27    $1,6.   2018    $2,1.  -       ,  , , ,     .       -1,    2011,          ,    ,     .          ,       .

     ࠖ   .      .     ,     ,  .         ,      . Ѡ ,            , 頖       .

    蠖  ࠖ    ,       . ʠ  , ,   ,    , -, -  .        ,     ,    -   .          ,       ,        .

           .

     ,       .    ,    2017  $16,2,  21% ,  2016.

 ࠖ   ,   20,     .        ,   . ,      2017  $6,6,   蠖 $2.      37% 2017,   蠖 27%.




1.1.  



       1970- .  2017    2  .

     ,   .[2 -     ISO 8373:2012.]    ()     ,     -  .

       頖 -   -,     .    ⠖  ABB (), FANUC (), Kawasaki (), KUKA Robotics (), NACHI (), OTC-DAIHEN (), Panasonic ( ), Universal Robotics (), Yaskawa (). -    .      .          .

           .

 2017    381.  ,  30% ,  2016 (. 1).  IFR, 2021      630. .

 ,      ,       (. 2).  2017      2098000,  15% ,  2016.  IFR,  2021       16% .






. 1.    , ..

:IFR






. 2.    , ..

:IFR




1.1.1.    


      -  (. 3).  2016    37%  262. .     , 2021       463. .         ꠖ      .        ,    ,     .

     ,    .  2017    33.  ,      66. .  20182021     42%.

  2017   46.  ⠖ 5.  ,   . IFR      2018 (44. .),    20192021    40%.






. 3.    , ..

:IFR



       ,     ,   , ,  ,  .   2017  73%   . 6- 7-    (11. .)  (8. .) (.4).






. 4.     

2017., ..

:IFR



        .     .     ,  2017    4% ,    (40. .  41. .).    18%    .

 , ,    : 28.  2015, 31. 2016, 33. 2017.              2010.

          :    6%  2016,        ,  .

     :     300% 2.   2016 8. 2017- (.5).






. 5.   - 

  20152017., ..

:IFR



.          .  2016    52%   , 2017 56% (.6).






. 6.   , 2017.

:IFR



 22%       ,   (78%)   , ,   .

     ,      .   2016    1%   - .

     2017 18%  2016  45566 ,      2000 (46986.)



.        ,       .      59%     138.  (. 7),       (112400.).     36%  ,     ,  ,  .






. 7.    , ..



    : 2017      72%  103200.      ,    ,   . ,             :     25%    2016,   35. .

  ,        . ,   ,       ,  -  ABB.   2005,      4500. Ƞ  8,     25. ,       .  2013    ,  Yaskawa, Epson, KUKA, Comau; 2015   Kawasaki Nachi, 2016-젖 Rethink Robotics.

         .          .   2013               .        :    ,  ,          ,   - ,      ,       ,      .




1.1.2.    


 ,   2017   ,  ,  ,  ,    (.8).

      :   2017  33%   ,  22% ,  2016.   . -,        ,       . -,     , ,  ,    .






. 8.    

, ..

:IFR



       .  ,                      40% 2030.

        .     ,    ,      ,     ,     .

       .     33% 2017    121300,   32%    .      , , , .           .             . , ,              .

          2016:   55%  10%  .  2018     (   ,  ).            4.0,   ,       ,    .




1.1.3.  


           ,   .        10. ,  .

 2017      85 10. ,      (2016 74 10. ).






. 9.   2017. :IFR



    頖 106 10. ,   蠖 91.   10.   75 (.9).

        , , , , .

        堖 710.  2016    631 10. , 2015-젖 531.     2010       .

    (658 10.  2017):  ,    ,  ,      .  2016     488 10. ,  ,       , 398.

    305, 蠖 301,  176 10. .

     97 10. .  2015            .






. 10.   

:IFR



    ,  3  2015.       212240 10. .




1.1.4.   


          , ,   ,        .         ,    .

     ,       :

    10   27   19992010[3 - Zierahn U., Gregory T., Arntz M. Racing with or Against the Machine? Evidence from Europe. ZEW Centre for European Economic Research. 2016[ ] URL: http://ftp.zew.de/pub/zew-docs/dp/dp16053.pdf (http://ftp.zew.de/pub/zew-docs/dp/dp16053.pdf).].

         [4 - Bassen J. Computers Dont Kill Jobs but Do Increase Inequality. Harvard Business Review. 2016[ ] URL: https://hbr.org/2016/03/computers-dont-kill-jobs-but-do-increase-inequality (https://hbr.org/2016/03/computers-dont-kill-jobs-but-do-increase-inequality).].

 ,    ,    ,  ,   [5 - Muro M., Andes S. Robots Seem toBe Improving Productivity, Not Costing Jobs. Harvard Business Review. 2015[ ] URL: https://hbr.org/2015/06/robots-seem-to-be-improving-productivity-not-costing-jobs (https://hbr.org/2015/06/robots-seem-to-be-improving-productivity-not-costing-jobs).].

   ,    ,      .

    ,    . ,     2008  355.   ,       50. .    2010      115.  ,        7.[6 - The Age ofAutomation: Artificial Intelligence, Robotics and the Future ofLow-Skilled Work. Royal Society for the encouragement ofArts, Manufactures and Commerce. September, 2017. [ ] URL: https://www.thersa.org/globalassets/pdfs/reports/rsa_the-age-of-automation-report.pdf (https://www.thersa.org/globalassets/pdfs/reports/rsa_the-age-of-automation-report.pdf).]

            [7 - Graetz G., Michaels G. Robots at work. Study for the Centre for Economic Performance at the London School ofEconomics. 2018[ ] URL: http://personal.lse.ac.uk/michaels/Graetz_Michaels_Robots.pdf (http://personal.lse.ac.uk/michaels/Graetz_Michaels_Robots.pdf).].

      (. 11).   20102015     13.   93.  .   2014     21. ,       3,4 3,5.      ,    9%          6%.




  .


   .

   ,     (https://www.litres.ru/alisa-konuhovskaya/rynok-robototehniki-ugrozy-i-vozmozhnosti-dlya-rossii/)  .

      Visa, MasterCard, Maestro,    ,   ,     ,  PayPal, WebMoney, ., QIWI ,       .



notes








1


Kara D. July 2018Robotics and Intelligent Systems Investments. The Robot Report [ ] URL: https://www.therobotreport.com/july-2018-robotics-and-intelligent-systems-investments (https://www.therobotreport.com/july-2018-robotics-and-intelligent-systems-investments).




2


    ISO 8373:2012.




3


Zierahn U., Gregory T., Arntz M. Racing with or Against the Machine? Evidence from Europe. ZEW Centre for European Economic Research. 2016[ ] URL: http://ftp.zew.de/pub/zew-docs/dp/dp16053.pdf (http://ftp.zew.de/pub/zew-docs/dp/dp16053.pdf).




4


Bassen J. Computers Dont Kill Jobs but Do Increase Inequality. Harvard Business Review. 2016[ ] URL: https://hbr.org/2016/03/computers-dont-kill-jobs-but-do-increase-inequality (https://hbr.org/2016/03/computers-dont-kill-jobs-but-do-increase-inequality).




5


Muro M., Andes S. Robots Seem toBe Improving Productivity, Not Costing Jobs. Harvard Business Review. 2015[ ] URL: https://hbr.org/2015/06/robots-seem-to-be-improving-productivity-not-costing-jobs (https://hbr.org/2015/06/robots-seem-to-be-improving-productivity-not-costing-jobs).




6


The Age ofAutomation: Artificial Intelligence, Robotics and the Future ofLow-Skilled Work. Royal Society for the encouragement ofArts, Manufactures and Commerce. September, 2017. [ ] URL: https://www.thersa.org/globalassets/pdfs/reports/rsa_the-age-of-automation-report.pdf (https://www.thersa.org/globalassets/pdfs/reports/rsa_the-age-of-automation-report.pdf).




7


Graetz G., Michaels G. Robots at work. Study for the Centre for Economic Performance at the London School ofEconomics. 2018[ ] URL: http://personal.lse.ac.uk/michaels/Graetz_Michaels_Robots.pdf (http://personal.lse.ac.uk/michaels/Graetz_Michaels_Robots.pdf).


